SMU SOE Seminar (Feb 4, 2020): A Randomized Missing Data Approach to Robust Filtering with Applications to Economics and Finance

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TOPIC:

A RANDOMIZED MISSING DATA APPROACH TO ROBUST FILTERING WITH APPLICATIONS TO ECONOMICS AND FINANCE

ABSTRACT We put forward a simple new approach to robust ﬁltering of state-space models, motivated by the idea that the inclusion of only a small fraction of available highly precise measurements can still extract most of the attainable eﬃciency gains for ﬁltering latent states, estimating model parameters, and producing out-of-sample forecasts. The new class of particle ﬁlters we develop aims to achieve a degree of robustness to outliers and model misspeciﬁcation by purposely randomizing the subset of utilized highly precise but possibly misspeciﬁed or outlier contaminated data measurements, while treating the rest as if missing. The arising robustness-eﬃciency trade-oﬀ is controlled by varying the fraction of randomly utilized measurements or the incurred relative eﬃciency loss from such randomized utilization of the available measurements. As an empirical illustration, we consider popular state space models for inﬂation and equity returns with stochastic volatility and document favorable performance of our robust particle ﬁlter and density forecasts on both simulated and real data. More generally, our randomization approach makes it easy to robustly incorporate highly informative but possibly contaminated modern “big data” streams for improved state-space ﬁltering and forecasting. Keywords: State space models, particle ﬁltering, robustness, outliers, misspeciﬁcation, stochastic volatility, realized volatility, return density forecasting, inﬂation forecasting. Click here to view the paper. Click here to view the CV.
		PRESENTER Dobrislav Dobrev Federal Reserve Board
		RESEARCH FIELDS Financial Econometrics in Data-Rich Environments High Frequency Trading
		DATE: 4 February 2020 (Tuesday)
		TIME: 4pm - 5.30pm
		VENUE: Meeting Room 5.1, Level 5 School of Economics Singapore Management University 90 Stamford Road Singapore 178903

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